Data content is stored and communicated to an increasing extent by contemporary human population, for example multimedia content via the Internet and wireless communication networks; such multimedia content often includes, for example images, video and audio, but is not limited thereto. The data content stored and communicated between devices, software applications, media systems and data services. During such storage and communication, situations arise where images and video are captured, scanned, transmitted, shared, watched and printed. However, such images and videos are demanding in respect of data memory capacity and communication system bandwidth that is utilized. When communication system bandwidth is limited, such images and videos take significant time to communicate. For addressing such storage requirements, it has been a customary practice to employ image and video encoding methods which also provide a degree of data compression. Some contemporary encoding standards for images and video are provided in Table 1.
TABLE 1Contemporary Encoding StandardsJPEGMPEG-1H.261WebPLucidJPEG2000MPEG-2H.263WebMGIFJPEG XRMPEG-4H.264PNGMPEG-4 AVCH.265 (HEVC)TIFFMPEG-4 MVCBMPMP3VC-1TheoraAACFLACOgg VorbisSpeex
Image and audio files are becoming larger as image quality is progressively improved, for example by adoption of high definition (HD) standards and high dynamic range (HDR). However, 3-dimensional (3-D) images, videos and audio are gaining increasing popularity which demands correspondingly more efficient encoding and decoding methods in encoders and decoders, namely “codecs”, to cope with associated increased quantities of data to be communicated and stored. However, it is highly desirable that encoding methods that provide a degree of data compression should be substantially lossless in relation to information content when generating the compressed data.
Conventional codecs are described in earlier published patent applications and granted patents, for example as provided in Table 2.
TABLE 2Earlier Publications Describing CodecsEarlier patents or patentapplicationsDetailsU.S. Pat. No. 5,832,130Samsung Electronics Co. Ltd.U.S. Pat. No. 7,379,496Microsoft Corp.GB2274754A1Samsung Electronics Co. Ltd.U.S. Pat. No. 6,529,634A1ThyagarajanU.S. Pat. No. 7,676,101Sony Corp.US2006/0204115A1Burazerovic: employs a single typeof encoding with variable parametersfor encoded blocks
In general, many known video codecs are not able to code efficiently extensive areas of images with substantially constant parameters whilst concurrently being able to encode highly spatially detailed areas of the images. It is customary practice to employ motion compensation in a form of prediction and prediction error coding methods based upon use of transformations, for example discrete cosine transform (DCT) and wavelet transformations. These transformations employ a process wherein portions of a given image, for example a still image or an image forming a part of a video sequence, are divided into blocks which are then subject to encoding processes. The blocks are, for example, 8×8 image elements, 4×4 image elements or similar. Such relatively smaller blocks are employed because larger sizes of blocks result in inefficient encoding processes, although 16×16 image element blocks are sometimes employed. According to contemporary known approaches to image encoding, when multiple different block sizes are used for encoding, it is customary practice to utilize a small variation in block sizes; moreover, block sizes are selected based upon how well movement can be compensated in an associated block area or based upon a encoding quality parameter, for example a target quality parameter. In general, higher encoded image quality requires smaller blocks which results in less data compression. Certain types of contemporary encoding can even result in an increase in data size, when error correction features such as parity codes and error correction codes are included.
From the foregoing, it will be appreciated that providing data compression of, for example, images and videos whilst preserving image quality is a contemporary problem which is not adequately addressed by known encoders and decoders, despite a large variety of codecs having been developed during recent decades. However, even bigger problems occur along the progress reached in sequencing human genomes and utilizing them in medical research and development. This is because of the increased need of storage and transfer of huge amounts of genomic data, which thus needs to be efficiently compressed. Yet further, Internet of Things (IoT) concerns devices that process large amounts of data, yet the individual batches of data are typically small in size. These problems raised by new, disruptive technologies and big data require efficient ways of compression which known coding technology has not been able to sufficiently address.
Finally, it should be appreciated that contemporary codecs are typically able to compress only one type of data whereas the embodiments pursuant to the disclosure are capable of processing all types of data content as will be described in the following: